Abstract
In this paper, we propose a new framework to predict visual scanpaths of observers while they freely watch a visual scene. The visual fixations are inferred from bottom-up saliency and several oculomotor biases. Bottom-up saliency is represented by a saliency map whereas the oculomotor biases (saccade amplitudes and saccade orientations) are modeled using public eye tracking datasets. Our experiments show that the simulated scanpaths exhibit similar trends of human eye movements in a free-viewing condition. The generated scanpaths are more similar to human scanpaths than those generated by two existing methods. In addition, we show that computing saliency maps from simulated visual scanpaths allows to outperform existing saliency models.
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